Identifying Structure across Pre-partitioned Data 

Zvika Marx
NYU 

joint work with Ido Dagan and Eli Shamir 

Friday, April 9
2:30PM          
Room 102       
Weaver Hall
251 Mercer Street
NYU, NYC, NYS 

ABSTRACT
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We propose an information-theoretic clustering approach that
incorporates a pre-known partition of the data, aiming to identify 
common clusters that cut across the given partition.  In the 
standard clustering setting the formation of clusters is guided by 
a single source of feature information.  The newly utilized pre-partition 
factor introduces an additional bias that counterbalances the impact 
of the features whenever they become correlated with this known partition.  
The resulting algorithmic framework was applied successfully to synthetic 
data, as well as to identifying text-based cross-religion correspondences.